[Patches] Unicode Character Name codec support

Bill Tutt billtut@microsoft.com
Thu, 11 May 2000 16:11:21 -0700


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This is all based on AMK's perfect_hash work and MAL's unicode-escape
decoding, so hopefully a wet signature isn't necessary.

This unicode-named codec also handles normal unicode-escapes since codecs
are not easily and usefully stackable, and not stacking them is more
effecient in any event.

An altertnative to this approach would be to stick the data in one .c file,
and move PyUnicode_DecodeNamedUnicodeEscape into the unicode-escape code.

Just as an informational matter, the hash table is 1.79 times bigger than
the # of unicode characters that have names.

Attached in the zip file are the requisite changes:

Files:
patch.txt:
Contains changes to the existing files in CVS for the following things:
Adds _ucn.c into the build gunk
Trivial patch to pcbuild.dsw not included on purpose since my Visual Studio
was making more changes than made me comfortable.

New files:
_ucn.c: Already generated file, should just drop into Modules\
_ucn.dsp: MSVC project file, drop into PCBuild, and insert into pcbuild.dsw,
and create a dependancy on python16.
test_ucn.py: Drop in Lib\test
unicode_named.py: Codec file, should be dropped into Lib\encodings

The following files are provided for informational purposes and as a
mechanism to explain how this was generated:
Suggestions of how or if this should be included in Python's build process
are greatly appreciated.

perfect_hash.py: A tweaked copy of AMK's perfect_hash.py that sucks in
UnicodeData.txt and generates _ucn.c.
perfhash.c:      A helper module for perfect_hash.py. This just lets the
generated C code be more effecient than AMK's original code.
UnicodeData.txt: Input file for perfect_hash.py

Usage of perfect_hash.py:
perfect_hash.py UnicodeData.txt > _ucn.c


Bill

Release info:
I confirm that, to the best of my knowledge and belief, this contribution is
free of any claims of third parties under copyright, patent or other rights
or interests ("claims"). To the extent that I have any such claims, I hereby
grant to CNRI a nonexclusive, irrevocable, royalty-free, worldwide license
to reproduce, distribute, perform and/or display publicly, prepare
derivative versions, and otherwise use this contribution as part of the
Python software and its related documentation, or any derivative versions
thereof, at no cost to CNRI or its licensed users, and to authorize others
to do so. I acknowledge that CNRI may, at its sole discretion, decide
whether or not to incorporate this contribution in the Python software and
its related documentation. I further grant CNRI permission to use my name
and other identifying information provided to CNRI by me for use in
connection with the Python software and its related documentation. 

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